Confidential Federated Learning — Live on Robinhood Chain

Robots that learnwithout sharingwhat they see.

Your robot sees everything. QUIVER lets it contribute to shared intelligence without ever transmitting a single frame of what it observed.

—
robots learning
—
model rounds
—
QUIV distributed
FOREVER
0
raw frames uploaded
Local Training/Intel TDX Enclaves/Differential Privacy/Traffic Shaping/Staked Validators/Confidential Settlement/0 Frames Transmitted/Local Training/Intel TDX Enclaves/Differential Privacy/Traffic Shaping/Staked Validators/Confidential Settlement/0 Frames Transmitted/
Participate

A role for everyone.

QUIV token — Robinhood Chain
ROLE 01

Enroll a Robot

Your robot trains locally and contributes encrypted updates to the shared model. Raw perception never leaves the device. Earn QUIV + USDC for every accepted round.

Enroll now
ROLE 02

Keep the Model Honest

Stake QUIV and review contribution quality. Catch model poisoning, earn protocol fees, and become the immune system of the robot-intelligence network.

Start validating
ROLE 03

License the Intelligence

Browse skill-models trained on diverse real-world robot experience — with full privacy provenance showing no raw footage was ever collected.

Browse models
Privacy Architecture

Six layers ofdefense-in-depth.

01
Local Training
Robots train on their own hardware. Raw sensor data never leaves the device — not encrypted in transit, simply never transmitted.
02
TEE Aggregation
Encrypted updates combine inside Intel TDX enclaves. No individual contribution is ever decrypted outside the attested environment.
03
Differential Privacy
Calibrated noise applied to the global model. No robot's environment can be reverse-engineered — a formal mathematical guarantee.
04
Traffic Shaping
Padded and scheduled uploads defeat traffic-analysis attacks. Observers cannot infer robot actions from encrypted network patterns.
05
Anti-Poisoning
Staked validators review every contribution. Model poisoning attempts result in stake slashing; honest validators earn protocol fees.
06
Confidential Settlement
Encrypted balances keep reward flows private. On-chain data reveals nothing about who contributed what.
The thesis

Privacy isthe unlock.

A hospital, a homeowner, an enterprise fleet manager can verify continuously that nothing the robot saw was ever transmitted — only mathematics about what it learned.

Revenue split
60%
Robot contributors
20%
Aggregators + validators + stakers
10%
Treasury
10%
Token burn